Scheduled Commit

data/clustering_battle-8d38bb89-1e1a-471a-8b9e-35c1f784690e.jsonl

@@ -0,0 +1 @@
+{"tstamp": 1722367036.7553, "task_type": "clustering", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "1e22b57c96ae43d8ba94cae6ac46e428", "0_model_name": "embed-english-v3.0", "0_prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "0_ncluster": 5, "0_output": "", "0_ndim": "2D (press for 3D)", "0_dim_method": "PCA", "0_clustering_method": "KMeans", "1_conv_id": "1d7ff0ec14534a8a8e417bc5e41188f7", "1_model_name": "GritLM/GritLM-7B", "1_prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "1_ncluster": 5, "1_output": "", "1_ndim": "2D (press for 3D)", "1_dim_method": "PCA", "1_clustering_method": "KMeans"}

data/clustering_individual-8d38bb89-1e1a-471a-8b9e-35c1f784690e.jsonl

@@ -30,3 +30,9 @@
 {"tstamp": 1722365293.3702, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722365293.2786, "finish": 1722365293.3702, "ip": "", "conv_id": "2d00a0ca7d964666be04860d6c0b93cf", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["Pikachu", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard"], "ncluster": 4, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
 {"tstamp": 1722365313.657, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722365313.5644, "finish": 1722365313.657, "ip": "", "conv_id": "2eda6a7402714107b73a1c42cad3f9d5", "model_name": "GritLM/GritLM-7B", "prompt": ["Pikachu", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard", "Pikachu", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
 {"tstamp": 1722365313.657, "task_type": "clustering", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722365313.5644, "finish": 1722365313.657, "ip": "", "conv_id": "2d00a0ca7d964666be04860d6c0b93cf", "model_name": "BAAI/bge-large-en-v1.5", "prompt": ["Pikachu", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard", "Pikachu", "Darth Vader", "Yoda", "Squirtle", "Gandalf", "Legolas", "Mickey Mouse", "Donald Duck", "Charizard"], "ncluster": 4, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722366957.629, "task_type": "clustering", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722366957.3301, "finish": 1722366957.629, "ip": "", "conv_id": "1e22b57c96ae43d8ba94cae6ac46e428", "model_name": "embed-english-v3.0", "prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722366957.629, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722366957.3301, "finish": 1722366957.629, "ip": "", "conv_id": "1d7ff0ec14534a8a8e417bc5e41188f7", "model_name": "GritLM/GritLM-7B", "prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "ncluster": 5, "output": "", "ndim": "3D (press for 2D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722367016.4134, "task_type": "clustering", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722367016.1449, "finish": 1722367016.4134, "ip": "", "conv_id": "1e22b57c96ae43d8ba94cae6ac46e428", "model_name": "embed-english-v3.0", "prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722367016.4134, "task_type": "clustering", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722367016.1449, "finish": 1722367016.4134, "ip": "", "conv_id": "1d7ff0ec14534a8a8e417bc5e41188f7", "model_name": "GritLM/GritLM-7B", "prompt": ["A", "O", "caldera", "composite", "shield", "elephant", "giraffe", "penguin", "tiger", "lion", "dolphin", "square", "rectangle", "circle", "hexagon", "triangle", "octagon", "Ursa Major", "Cygnus", "Cassiopeia", "Leo", "Scorpius", "Taurus", "Orion"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722367072.765, "task_type": "clustering", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1722367071.9605, "finish": 1722367072.765, "ip": "", "conv_id": "49918e2cfa004e65b3d3d613733b7f66", "model_name": "text-embedding-3-large", "prompt": ["mathematics", "literature", "Norse", "Hindu", "contemporary", "salsa", "ballet", "hip-hop", "ballroom", "jazz", "conscientiousness", "openness", "neuroticism", "extroversion", "stomach", "lungs", "pancreas", "heart", "brain"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}
+{"tstamp": 1722367072.765, "task_type": "clustering", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722367071.9605, "finish": 1722367072.765, "ip": "", "conv_id": "bfefbf9a7a1446ffbf84e23200f20d1f", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": ["mathematics", "literature", "Norse", "Hindu", "contemporary", "salsa", "ballet", "hip-hop", "ballroom", "jazz", "conscientiousness", "openness", "neuroticism", "extroversion", "stomach", "lungs", "pancreas", "heart", "brain"], "ncluster": 5, "output": "", "ndim": "2D (press for 3D)", "dim_method": "PCA", "clustering_method": "KMeans"}

data/retrieval_individual-8d38bb89-1e1a-471a-8b9e-35c1f784690e.jsonl

@@ -70,3 +70,5 @@
 {"tstamp": 1722366414.2932, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1722366413.3732, "finish": 1722366414.2932, "ip": "", "conv_id": "3f5d842f29464f66b1432b7a355fab52", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "Research introducing a technique where visual vocabulary learned from image tags is used for generating captions for novel objects.", "output": [["Research introducing a technique where visual vocabulary learned from image tags is used for generating captions for novel objects.", "Title: Young massive star clusters in the era of the Hubble Space Telescope\n\nAbstract: The Hubble Space Telescope (HST) has been instrumental in the discovery of large numbers of extragalactic young massive star clusters (YMCs), often assumed to be proto-globular clusters (GCs). As a consequence, the field of YMC formation and evolution is thriving, generating major breakthroughs as well as controversies on annual (or shorter) time-scales. Here, I review the long-term survival chances of YMCs, hallmarks of intense starburst episodes often associated with violent galaxy interactions. In the absence of significant external perturbations, the key factor determining a cluster's long-term survival chances is the shape of its stellar initial mass function (IMF). It is, however, not straightforward to assess the IMF shape in unresolved extragalactic YMCs. I also discuss the latest progress in worldwide efforts to better understand the evolution of entire cluster populations, predominantly based on HST observations, and conclude that there is an increasing body of evidence that GC formation appears to be continuing until today; their long-term evolution crucially depends on their environmental conditions, however."]], "corpus": "arxiv"}
 {"tstamp": 1722366808.573, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722366806.2538, "finish": 1722366808.573, "ip": "", "conv_id": "8b7dbc40208847bdbcdaba8aafdeee5a", "model_name": "GritLM/GritLM-7B", "prompt": "hi how are you ", "output": [["hi how are you ", "Hi, How Are You\n\nHi, How Are You: The Unfinished Album is the sixth self-released music cassette album by singer-songwriter Daniel Johnston, recorded in September 1983. The subtitle refers to the length of the album; Johnston had intended for it to be an hour-long release, as a majority of his earlier releases were.\nBackground"]], "corpus": "wikipedia"}
 {"tstamp": 1722366808.573, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722366806.2538, "finish": 1722366808.573, "ip": "", "conv_id": "411e98668a6e4744bfdb95ba014a56c8", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "hi how are you ", "output": [["hi how are you ", "Howdy\n\nHowdy is an informal salutation in the English language often used in the Southern United States. Originally a shortened form of the inquiry How do ye?, it was first used in Southern England in the 18th century.\nEtymology\nThe word derives from the phrase \"How do ye?,\" which was used in late 16th century England to ask about others' health. The phrase saw increasing degrees of dialectal contraction over time, first being contracted to \"how dee,\" then to \"howdy'ee,\" and finally to its modern form. Despite the etymology of the term, its modern usage is as a greeting and not as an inquiry.\nUse in different states\nIn many rural Southern and Western states, especially in Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Texas, and Wyoming, howdy is commonly used in casual contexts as a standard greeting. The term is commonly associated in popular culture specifically with the state of Texas, and the usage of the term is a significant and recognizable component of Texan English. Howdy is also the official greeting of Texas A&M University, though the two are not always automatically associated."]], "corpus": "wikipedia"}
+{"tstamp": 1722367064.3504, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722367064.0986, "finish": 1722367064.3504, "ip": "", "conv_id": "a137ffc84eff4239aa7a60386c425ec6", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "the rule of the three rightly guided caliphs was called", "output": [["the rule of the three rightly guided caliphs was called", "Rashidun\n\nThe Rashidun () are the first four caliphs (lit.: 'successors') who led the Muslim community following the death of Muhammad: Abu Bakr (), Umar (), Uthman (), and Ali ().\nThe reign of these caliphs, called the Rashidun Caliphate (632–661), is considered in Sunni Islam to have been 'rightly guided' (Arabic: ), meaning that it constitutes a model () to be followed and emulated from a religious point of view.\nHistory\nThe first four caliphs who succeeded Muhammad are known as the Rashidun (rightly-guided) Caliphs.\nAbu Bakr (; )\nUmar ibn al-Khattab (; ) – often known simply as Umar or Omar\nUthman ibn Affan (; ) – often known simply as Uthman, Othman, or Osman\nAli ibn Abi Talib (; ) – often known simply as Ali\nThe succession to Muhammad is the central issue that divides the Muslim community. Sunni Islam, according to the author Carl Ernst, accepts the political status quo of their succession, regardless of its justice, whereas Shia Muslims largely reject the legitimacy of the first three caliphs, and maintain that Muhammad had appointed Ali as his successor."]], "corpus": "wikipedia"}
+{"tstamp": 1722367064.3504, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722367064.0986, "finish": 1722367064.3504, "ip": "", "conv_id": "bb4de3c49176434fbe81b5d300079d17", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "the rule of the three rightly guided caliphs was called", "output": [["the rule of the three rightly guided caliphs was called", "Rashidun\n\nThe Rashidun () are the first four caliphs (lit.: 'successors') who led the Muslim community following the death of Muhammad: Abu Bakr (), Umar (), Uthman (), and Ali ().\nThe reign of these caliphs, called the Rashidun Caliphate (632–661), is considered in Sunni Islam to have been 'rightly guided' (Arabic: ), meaning that it constitutes a model () to be followed and emulated from a religious point of view.\nHistory\nThe first four caliphs who succeeded Muhammad are known as the Rashidun (rightly-guided) Caliphs.\nAbu Bakr (; )\nUmar ibn al-Khattab (; ) – often known simply as Umar or Omar\nUthman ibn Affan (; ) – often known simply as Uthman, Othman, or Osman\nAli ibn Abi Talib (; ) – often known simply as Ali\nThe succession to Muhammad is the central issue that divides the Muslim community. Sunni Islam, according to the author Carl Ernst, accepts the political status quo of their succession, regardless of its justice, whereas Shia Muslims largely reject the legitimacy of the first three caliphs, and maintain that Muhammad had appointed Ali as his successor."]], "corpus": "wikipedia"}

data/sts_battle-8d38bb89-1e1a-471a-8b9e-35c1f784690e.jsonl

@@ -0,0 +1 @@
+{"tstamp": 1722367137.3081, "task_type": "sts", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "6c9e9c68281640ef836c0c53aeeb88bc", "0_model_name": "voyage-multilingual-2", "0_txt0": "Five women wearing red formal ball gowns are standing together.", "0_txt1": "Five women with red and black halter tops and red and black miniskirts wearing red and white shoes.", "0_txt2": "A group of women are dressed alike.", "0_output": "", "1_conv_id": "c9c382e420cf4cf0b6d571b54b35ee29", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_txt0": "Five women wearing red formal ball gowns are standing together.", "1_txt1": "Five women with red and black halter tops and red and black miniskirts wearing red and white shoes.", "1_txt2": "A group of women are dressed alike.", "1_output": ""}

data/sts_individual-8d38bb89-1e1a-471a-8b9e-35c1f784690e.jsonl

@@ -2,3 +2,5 @@
 {"tstamp": 1722361062.1103, "task_type": "sts", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722361061.4332, "finish": 1722361062.1103, "ip": "", "conv_id": "9a17451afc00432d8d948ed9b4423baa", "model_name": "Salesforce/SFR-Embedding-2_R", "txt0": "Forecasting has been easier recently due to the updated process we have today.", "txt1": "The estimating challenges retailers go up against have been intensified as of late by item multiplication in practically every classification.", "txt2": "The forecasting challenges retailers confront have been amplified in recent years by product proliferation in almost every category.", "output": ""}
 {"tstamp": 1722363533.0121, "task_type": "sts", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1722363532.8625, "finish": 1722363533.0121, "ip": "", "conv_id": "a618ea1a2ed940ceb55925d1dac49f78", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "txt0": "She trained a neural network to recognize faces.", "txt1": "She developed an AI to identify human features.", "txt2": "She trained a new recruit to recognize faces.", "output": ""}
 {"tstamp": 1722363533.0121, "task_type": "sts", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1722363532.8625, "finish": 1722363533.0121, "ip": "", "conv_id": "996ff2d1e9ac48b29b9590a71fbe6a53", "model_name": "intfloat/e5-mistral-7b-instruct", "txt0": "She trained a neural network to recognize faces.", "txt1": "She developed an AI to identify human features.", "txt2": "She trained a new recruit to recognize faces.", "output": ""}
+{"tstamp": 1722367117.2478, "task_type": "sts", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722367116.9614, "finish": 1722367117.2478, "ip": "", "conv_id": "6c9e9c68281640ef836c0c53aeeb88bc", "model_name": "voyage-multilingual-2", "txt0": "Five women wearing red formal ball gowns are standing together.", "txt1": "Five women with red and black halter tops and red and black miniskirts wearing red and white shoes.", "txt2": "A group of women are dressed alike.", "output": ""}
+{"tstamp": 1722367117.2478, "task_type": "sts", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1722367116.9614, "finish": 1722367117.2478, "ip": "", "conv_id": "c9c382e420cf4cf0b6d571b54b35ee29", "model_name": "intfloat/multilingual-e5-large-instruct", "txt0": "Five women wearing red formal ball gowns are standing together.", "txt1": "Five women with red and black halter tops and red and black miniskirts wearing red and white shoes.", "txt2": "A group of women are dressed alike.", "output": ""}